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Creators/Authors contains: "Haber, Lisa T"

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  1. Disturbances from insect pests threaten ecologically and economically important goods and services supplied by forests, including wood production and carbon sequestration. We highlight the factors that influence these services’resistance, a term quantifying the initial response to disturbance. Insects inflict damage through a range of mechanisms, prompting distinct plant physiological responses that scale to influence ecosystem processes and, with time, goods and services. The degree and timing of tree mortality and defoliation affect the amount of residual vegetation available to support compensatory wood production and influence carbon sequestration by changing rates of detritus‐fueled decomposition. Compounding, or sequential, insect attacks may prime a forest for additional disturbance, further eroding wood production and carbon sequestration. Forest management practices that promote biological and structural diversity, and augment or retain limiting biological and nutrient resources, may buffer against the effects of insect pests on wood production and carbon sequestration. 
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    Free, publicly-accessible full text available June 16, 2026
  2. Across the globe, the forest carbon sink is increasingly vulnerable to an expanding array of low- to moderate-severity disturbances. However, some forest ecosystems exhibit functional resistance (i.e., the capacity of ecosystems to continue functioning as usual) following disturbances such as extreme weather events and insect or fungal pathogen outbreaks. Unlike severe disturbances (e.g., stand-replacing wildfires), moderate severity disturbances do not always result in near-term declines in forest production because of the potential for compensatory growth, including enhanced subcanopy production. Community-wide shifts in subcanopy plant functional traits, prompted by disturbance-driven environmental change, may play a key mechanistic role in resisting declines in net primary production (NPP) up to thresholds of canopy loss. However, the temporal dynamics of these shifts, as well as the upper limits of disturbance for which subcanopy production can compensate, remain poorly characterized. In this study, we leverage a 4-year dataset from an experimental forest disturbance in northern Michigan to assess subcanopy community trait shifts as well as their utility in predicting ecosystem NPP resistance across a wide range of implemented disturbance severities. Through mechanical girdling of stems, we achieved a gradient of severity from 0% (i.e., control) to 45, 65, and 85% targeted gross canopy defoliation, replicated across four landscape ecosystems broadly representative of the Upper Great Lakes ecoregion. We found that three of four examined subcanopy community weighted mean (CWM) traits including leaf photosynthetic rate ( p = 0.04), stomatal conductance ( p = 0.07), and the red edge normalized difference vegetation index ( p < 0.0001) shifted rapidly following disturbance but before widespread changes in subcanopy light environment triggered by canopy tree mortality. Surprisingly, stimulated subcanopy production fully compensated for upper canopy losses across our gradient of experimental severities, achieving complete resistance (i.e., no significant interannual differences from control) of whole ecosystem NPP even in the 85% disturbance treatment. Additionally, we identified a probable mechanistic switch from nutrient-driven to light-driven trait shifts as disturbance progressed. Our findings suggest that remotely sensed traits such as the red edge normalized difference vegetation index (reNDVI) could be particularly sensitive and robust predictors of production response to disturbance, even across compositionally diverse forests. The potential of leaf spectral indices to predict post-disturbance functional resistance is promising given the capabilities of airborne to satellite remote sensing. We conclude that dynamic functional trait shifts following disturbance can be used to predict production response across a wide range of disturbance severities. 
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  3. Markel, Scott (Ed.)
    The opportunity to participate in and contribute to emerging fields is increasingly prevalent in science. However, simply thinking about stepping outside of your academic silo can leave many students reeling from the uncertainty. Here, we describe 10 simple rules to successfully train yourself in an emerging field, based on our experience as students in the emerging field of ecological forecasting. Our advice begins with setting and revisiting specific goals to achieve your academic and career objectives and includes several useful rules for engaging with and contributing to an emerging field. 
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  4. null (Ed.)
  5. *Differential disturbance severity effects on forest vegetation structure, species diversity, and net primary production (NPP) have been long theorized and observed. Here, we examined these factors concurrently to explore the potential for a mechanistic pathway linking disturbance severity, changes in light environment, leaf functional response, and wood NPP in a temperate hardwood forest. *Using a suite of measurements spanning an experimental gradient of tree mortality, we evaluated the direction and magnitude of change in vegetation structural and diversity indexes in relation to wood NPP. Informed by prior observations, we hypothesized that forest structural and species diversity changes and wood NPP would exhibit either a linear, unimodal, or threshold response in relation to disturbance severity. We expected increasing disturbance severity would progressively shift subcanopy light availability and leaf traits, thereby coupling structural and species diversity changes with primary production. *Linear or unimodal changes in three of four vegetation structural indexes were observed across the gradient in disturbance severity. However, disturbance-related changes in vegetation structure were not consistently correlated with shifts in light environment, leaf traits, and wood NPP. Species diversity indexes did not change in response to rising disturbance severity. *We conclude that, in our study system, the sensitivity of wood NPP to rising disturbance severity is generally tied to changing vegetation structure but not species diversity. Changes in vegetation structure are inconsistently coupled with light environment and leaf traits, resulting in mixed support for our hypothesized cascade linking disturbance severity to wood NPP. 
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  6. null (Ed.)
    Abstract. The fortedata R package is an open data notebook from the Forest Resilience ThresholdExperiment (FoRTE) – a modeling and manipulative field experiment that teststhe effects of disturbance severity and disturbance type on carbon cyclingdynamics in a temperate forest. Package data consist of measurements ofcarbon pools and fluxes and ancillary measurements to help analyze andinterpret carbon cycling over time. Currently the package includes data andmetadata from the first three FoRTE field seasons, serves as a central,updatable resource for the FoRTE project team, and is intended as a resourcefor external users over the course of the experiment and in perpetuity.Further, it supports all associated FoRTE publications, analyses, andmodeling efforts. This increases efficiency, consistency, compatibility, and productivity while minimizing duplicated effort and error propagation thatcan arise as a function of a large, distributed and collaborative effort.More broadly, fortedata represents an innovative, collaborative way of approachingscience that unites and expedites the delivery of complementary datasets tothe broader scientific community, increasing transparency andreproducibility of taxpayer-funded science. The fortedata package is available via GitHub:https://github.com/FoRTExperiment/fortedata (last access: 19 February 2021), and detaileddocumentation on the access, used, and applications of fortedata are available athttps://fortexperiment.github.io/fortedata/ (last access: 19 February 2021). The first publicrelease, version 1.0.1 is also archived athttps://doi.org/10.5281/zenodo.4399601 (Atkins et al., 2020b). All data products are also available outside of thepackage as .csv files: https://doi.org/10.6084/m9.figshare.13499148.v1 (Atkins et al., 2020c). 
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  7. null (Ed.)